AI Strategy
A useful AI strategy is short. It states where the company expects AI to change economics, what it will not attempt, what has to be true operationally, and in what order things happen.
Updated 3 September 2026
This hub covers strategy that maps to delivery: readiness, sequencing, operating model, governance under the EU AI Act, and the failure patterns worth avoiding.
A five-part AI strategy framework — economic thesis, portfolio, operating model, governance and measurement — designed for mid-market companies rather than global enterprises.
A workable AI strategy has five parts: an economic thesis stating where AI is expected to change unit costs or capacity; a prioritized portfolio of specific wor…
The dimensions of AI readiness — data, process, systems, skills, governance and change capacity — how to score them, and how readiness should influence sequencing.
An AI readiness assessment scores six dimensions: data availability and quality, process stability, systems and integration access, skills and capacity, governa…
A twelve-month AI implementation roadmap for mid-market companies: what happens in each quarter, what gates each stage, and the signals that you are moving too fast.
A realistic first-year AI roadmap runs discovery and baseline measurement in the first six to eight weeks, a single reversible production workflow by the end of…
Merjora scores readiness alongside opportunity value, so sequencing reflects what your organisation can actually absorb.
Assess your AI readinessEditorial standard. Merjora publishes analysis, frameworks and publicly documented examples. We do not publish invented statistics, unattributed benchmarks or unverified customer stories.